Method and system for sensor monitoring and analysis

ABSTRACT

A method for monitoring performance of at least one component on a moving platform, the method including receiving sensor data for the at least one component, along with supplemental data, at a processing node; and processing the sensor data, the processing using the supplemental data to filter the sensor data.

FIELD OF THE DISCLOSURE

The present disclosure relates to sensor systems and in particularrelates to sensor systems for tire and bearing monitoring on a transporttrailer.

BACKGROUND

An important area for the maintenance of a fleet of transportationvehicles involves tire and wheel bearings within vehicles. This isparticularly true of trailers, since such trailers are generallyequipped with less sophisticated sensors from an electronics point ofview.

In today's systems, inspection and maintenance of tires and wheelbearings is done manually at regular intervals. The intervals could bebased on a combination of mileage and time. However, manual inspectionof tires and wheel bearings may depend on the skill of the operator andmay be error prone. Furthermore, the inspection typically occurs whenthe trailer or vehicle is stationary and therefore is merely a snapshotof the condition of the tire and wheel bearings. This may cause errors,especially when components are not easily visible and there is generallyno indication of impending failure.

Rotating components such as tires and wheel bearings (bearings) performunder significant stress, and are generally overdesigned so thatcatastrophic failure is mitigated. However, even with suchconsiderations, economic pressures tend to cause some lower integritycomponents to be installed. For example, a tire carcass that comprises aloadbearing component such as the bead and chords is often “recapped” or“retreaded” after a thorough cleaning and inspection of the carcasscondition. However, unlike a new tire, a cap component has a lowerintegrity and it is not uncommon for separation or delamination tooccur, resulting in overheating and destructive shedding of some or allof the tire.

While tire pressure monitoring systems (TPMS) allow an operator tomonitor tire pressures in a vehicle, such TPMS systems only providealarms after a tire suddenly loses pressure or blows. This does not dealwith bearing degradation or tire delamination issues.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure will be better understood with reference to thedrawings, in which:

FIG. 1 is a block diagram showing an example gateway and sensor modulecapable of being used in accordance with the embodiments of the presentdisclosure;

FIG. 2 is a block diagram showing an example environment for a gatewayand sensor apparatus in accordance with the embodiments of the presentdisclosure;

FIG. 3 is a block diagram of a trailer showing one wheel assembly in anexpanded view;

FIG. 4 is a process diagram showing a process at a sensor hub or gatewayfor providing sensor and supplemental data to a processing node;

FIG. 5 is a process diagram showing a process at a processing node forprocessing sensor and supplemental data; and

FIG. 6 is a block diagram of an example computing device capable ofbeing used in accordance with the embodiments of the present disclosure.

DETAILED DESCRIPTION OF THE DRAWINGS

The present disclosure provides a method for monitoring performance ofat least one component on a moving platform, the method comprising:receiving sensor data for the at least one component, along withsupplemental data, at a processing node; and processing the sensor data,the processing using the supplemental data to filter the sensor data.

The present disclosure further provides a processing node for monitoringperformance of at least one component on a moving platform, theprocessing node comprising: a processor; and a communications subsystem,wherein the processing node is configured to: receive sensor data forthe at least one component, along with supplemental data; and processthe sensor data, the processing using the supplemental data to filterthe sensor data.

The present disclosure further provides a computer readable medium forstoring instruction code, which, when executed by a processor on aprocessing node are configured for monitoring performance of at leastone component on a moving platform, the instruction code causing theprocessing node to: receive sensor data for the at least one component,along with supplemental data; and process the sensor data, theprocessing using the supplemental data to filter the sensor data.

In accordance with one embodiment of the present disclosure, inspectionand maintenance for rolling components such as tires and bearings isaugmented by developing a sensor network to monitor bearing conditions,including temperature and vibration, wheel assembly vibration, as wellas tire pressure and temperature. The results of such monitoring may beaggregated and the data processed to alert an operator and/or a fleetmanager when inspection and maintenance is required.

The present disclosure is provided below with regard to a trailer.However, in other embodiments other vehicles or equipment could equallybenefit from the disclosure provided herein. Therefore, the use of thesensors on the trailer is merely provided as an example.

In accordance with the embodiments of the disclosure provided below, asensor system is provided on a trailer. Such a sensor system mayinclude, but is not limited to, wheel bearing sensors that may includetemperature sensors and accelerometers, tire pressure monitoringsensors, and/or acoustic sensors. Such sensors may record readings oftire, bearing and wheel assembly data at pre-determined intervals. Forexample, the readings may be taken every five minutes in someembodiments.

The sensor data, including temperature information, acceleration orvibration information, acoustic information among other data, could besent to a wireless gateway associated with the sensor system.

The wireless gateway may periodically upload the sensor data to a cloudor server. The uploading may occur in various manners. For example, in afirst embodiment, raw data may be uploaded at regular intervals. Inother embodiments security and/or compression could be applied to thedata. In still further embodiments, raw data may be collected anduploaded only after a trip has finished. In some cases, the raw data maybe processed at the sensor system, and any anomalous behavior maytrigger an alarm immediately. Other examples for data uploading arepossible.

In addition to the above sensors, a micro-electromechanical (MEMS)sensor may be used to detect out of balance components and may alert asystem to impending failure, for example due to partial separation ordelamination of the tread of the tire.

Further, accelerometer data may contain acoustic information. Althoughthis appears as noise in the acceleration spectrum relevant to the wheelfrequencies, such information may comprise higher frequency componentswhich are representative of tire noise over the road as well as bearingnoise. This information may be extracted, for example using the FastFourier Transform, and the spectral data may be used to monitor a changein the condition of the rotating assembly well in advance ofcatastrophic failure.

For example, the data may indicate that a simple wheel change willalleviate an impending tire failure from increased imbalance. Sincebearing performance is directly affected by offset loads due toimbalance, an early remedy may result in greatly reduced wear andsubsequent maintenance downtime.

Also, bearings are known to exhibit acoustic noise in the ultrasonicacoustic range as part of normal operations and this may be detected byan accelerometer or other microphonic techniques.

In further embodiments, other sensors may also be incorporated into thesystem. For example, strain gauges or sensors that monitor brake wearcould be used. Brake wear sensors may issue warnings when brakes areworn below a safe minimum or worn unevenly, and provide an indication asto when brakes may require maintenance.

In other cases, supplemental data such as position/location fixes,visual cues, environmental temperature, pressure or other readings maybe used in conjunction with the bearing and tire sensors. The use ofsuch supplemental data can be used to filter results and enhance theprediction of component wear and potential failure.

The above is implemented on a vehicle or trailer using a sensor system.One sensor system is shown with regard to FIG. 1. The sensor system ofFIG. 1 is however merely an example and other sensor systems couldequally be used in accordance with the embodiments of the presentdisclosure.

Reference is now made to FIG. 1, which shows an example sensor system.The sensor system of FIG. 1 includes a gateway 110, which can be anycomputing device or network node. In some embodiments, gateway 110 mayalso be referred to as a hub. Such a computing device or network nodemay include any type of electronic device, including but not limited to,mobile devices such as smartphones or cellular telephones. Examples canfurther include fixed or mobile devices, such as Internet of Things(IOT) devices, endpoints, home automation devices, medical equipment inhospital or home environments, inventory tracking devices, environmentalmonitoring devices, energy management devices, infrastructure managementdevices, vehicles or devices for vehicles, fixed electronic devices,among others.

Gateway 110 comprises a processor 120 and at least one communicationssubsystem 130, where the processor 120 and communications subsystem 130cooperate to perform the methods of the embodiments described herein.The communications subsystem 130 may, in some embodiments, comprisemultiple subsystems, for example different radio technologies.

The communications subsystem 130 allows gateway 110 to communicate withother devices or network elements. The communications subsystem 130 mayuse one or more of a variety of communications types, including but notlimited to cellular, satellite, Bluetooth™, Bluetooth™ Low Energy (BLE),Wi-Fi, wireless local area network (WLAN), wireless personal areanetworks (WPAN), near field communications (NFC), ZigBee or any otherIEEE 802.15 low power technology, wired connections such as Ethernet orfiber, among other options.

As such, a communications subsystem 130 for wireless communications willtypically have one or more receivers and transmitters, as well asassociated components such as one or more antenna elements, localoscillators (LOs), and may include a processing module such as a digitalsignal processor (DSP). As will be apparent to those skilled in thefield of communications, the particular design of the communicationsubsystem 130 will be dependent upon the communication network orcommunication technology on which the sensor apparatus is intended tooperate.

One or more of the radios within the communications subsystem 130 mayinclude a radio controller 132. Such a radio controller can operate todetermine if a radio within the communications subsystem 130 isreceiving signals that need to be processed in one embodiment. Forexample, the radio controller 132 can detect if BLE communications fromanother component of the sensor system are trying to communicate withthe gateway 110.

The processor 120 generally controls the overall operation of thegateway 110 and is configured to execute programmable logic, which maybe stored, along with data, using memory 140. Memory 140 can be anytangible, non-transitory computer readable storage medium, including butnot limited to optical (e.g., CD, DVD, etc.), magnetic (e.g., tape),flash drive, hard drive, or other memory known in the art. In oneembodiment, the processor function may be implemented entirely inhardware, for example using a gate array, without any necessarilyalterable control instructions stored in memory. This has the advantagethat operation may be significantly faster than a software or firmwarecontrolled implementation.

Alternatively, or in addition to memory 140, gateway 110 may access dataor programmable logic from an external storage medium, for examplethrough the communications subsystem 130.

In the embodiment of FIG. 1, gateway 110 may utilize a plurality ofsensors to which it is coupled, which may either be part of gateway 110in some embodiments or may communicate with gateway 110 in otherembodiments. For internal sensors, processor 120 may receive input froma sensor subsystem 150.

For external sensors, sensors 152 and 154 are shown in the embodiment ofFIG. 1.

Examples of sensors include, but are not limited to, a positioningsensor, a vibration sensor, a temperature sensor, one or more imagesensors, accelerometer, light sensors, gyroscopic sensors, acousticsensors, or other sensors. Other sensors may be any sensor that iscapable of reading or obtaining data that may be useful for gateway 110.However, such list of sensors is merely provided as an example, and inother embodiments different sensors or a subset of sensors may be used.

In other embodiments, gateway 110 may not have any sensors, eitherinternal or external, connected directly to it. For example, in someembodiments, gateway 110 may instead be coupled to the sensors andcommunicate with sensor modules, as described below.

In one embodiment, the gateway may read the sensors. For example,gateway 110 may send a page or trigger to a sensor 152 and receive aresponse in return.

In other embodiments, sensor 152 may communicate with gateway 110without a page or other message.

Further, in some embodiments, sensor 152 may be capable of autonomouslygenerating a request with gateway 110 based on a detection at the sensorof an alarm condition or out-of-bounds condition. In a sensor system,such sensor autonomy may be useful to present an alert condition thatcan be serviced by the gateway 110.

Communications between the various elements of gateway 110 may bethrough an internal bus 158 in one embodiment. However, other forms ofcommunication are possible.

A sensor system may further include one or more sensor modules. A sensormodule is a system that allows communication from various sensors, wheredata can be received, stored, compiled, and/or processed prior to beingpassed to another element in the system, such as gateway 110.

For example, in the embodiment of FIG. 1, a sensor module 160 is shown.The sensor module 160 comprises a processor 162 and at least onecommunications subsystem 170, where the processor 162 and communicationssubsystem 172 cooperate to perform the methods of the embodimentsdescribed herein. The communications subsystem 170 may, in someembodiments, comprise multiple subsystems, for example different radiotechnologies.

The sensor module of FIG. 1 is however merely an example, and in otherembodiments may have a different configuration.

The communications subsystem 170 allows the sensor module 160 tocommunicate with other devices or network elements. The Communicationssubsystem 170 may use one or more of a variety of communications types,but would typically use short range communication such as, but notlimited to Bluetooth™, BLE, Wi-Fi, WLAN, WPAN, NFC, ZigBee or other IEEE802.15 low power technology, or wired connections such as Ethernet orfiber, among other options.

As with the communications subsystem 130, the communications subsystem170 will typically have one or more receivers and transmitters, as wellas associated components such as one or more antenna elements, localoscillators (LOs), and may include a processing module such as a digitalsignal processor (DSP). Again, the particular design of thecommunication subsystem 170 will be dependent upon the communicationnetwork or communication technology on which the sensor module isintended to operate.

One or more of the radios within the communications subsystem 170 mayinclude a radio controller 172. Such a radio controller can operate todetermine if a radio within the communications subsystem 170 isreceiving signals that need to be processed in one embodiment. Forexample, radio controller 172 can detect if BLE communications fromanother component of the sensor system is being used to try tocommunicate with the sensor module 160.

Processor 162 generally controls the overall operation of the sensormodule 160 and is configured to execute programmable logic, which may bestored, along with data, using memory 180. Memory 180 can be anytangible, non-transitory computer readable storage medium, including butnot limited to optical (e.g., CD, DVD, etc.), magnetic (e.g., tape),flash drive, hard drive, or other memory known in the art. In oneembodiment, processor 162 may also be implemented entirely in hardwareand not require any stored program to execute logic functions.

Alternatively, or in addition to memory 180, the sensor module 160 mayaccess data or programmable logic from an external storage medium, forexample through communications subsystem 170.

In the embodiment of FIG. 1, sensor module 160 may utilize a pluralityof sensors, which may either be part of sensor module 160 in someembodiments or may communicate with sensor module 160 in otherembodiments. For internal sensors, processor 162 may receive input froma sensor subsystem 164.

For external sensors, sensors 166 and 168 are shown in the embodiment ofFIG. 1.

In one embodiment, the sensor module 160 may read the sensors. Forexample, sensor module 160 may send a page to a sensor 166 and receive aresponse in return.

In other embodiments, sensor 166 may communicate with sensor module 160without a page or other message.

Further, in some embodiments, sensor 166 may be capable of autonomouslygenerating a request with sensor module 160 based on a detection at thesensor of an alarm condition or out-of-bounds condition. In a sensorsystem, such sensor autonomy may be useful to present an alert conditionthat can be serviced by sensor module 160 and/or the gateway 110.

Gateway 110 may communicate with zero, one, or a plurality of sensormodules. In the example of FIG. 1, in addition to sensor module 160,gateway 110 communicates with sensor modules 190 and 192.

In a sensor system, typically the gateway 110 will communicate withexternal network resources, while sensor module 160 will typicallycommunicate internally, for example with the gateway 110, other sensormodules, or sensors.

The sensor system, including gateway 110, may be affixed to any fixed ormoving platform. For example, gateway 110 may be affixed to shippingcontainers, truck trailers, truck cabs in one embodiment. In otherembodiments, gateway 110 may be affixed to any vehicle, including motorvehicles (e.g., automobiles, cars, trucks, buses, motorcycles, etc.),aircraft (e.g., airplanes, unmanned aerial vehicles, unmanned aircraftsystems, drones, helicopters, balloons, etc.), spacecraft (e.g.,spaceplanes, space shuttles, space capsules, space stations, satellites,etc.), watercraft (e.g., ships, boats, hovercraft, submarines, etc.),railed vehicles (e.g., trains and trams, etc.), pedestrians and bicyclesand other types of vehicles including any combinations of any of theforegoing, whether currently existing or after arising, among others. Asused herein, a vehicle, container, trailer or cab may all be referred toas a moving platform.

In other cases, the gateway 110 could be carried by a user.

In other cases, the gateway 110 may be affixed to stationary objectsincluding buildings, lamp posts, fences, cranes, temporary fixtures suchas emergency shelters and tents, among other options.

Such a sensor system, and specifically the gateway 110, sensor modules160, 190 or 192, or sensors 152, 154, 166 or 168 may be power limiteddevices. For example, gateway 110 could be a battery-operated devicethat can be affixed to a shipping container or trailer in someembodiments. Other limited power sources could include any limited powersupply, such as a small generator or dynamo, a fuel cell, solar power,amongst other options.

In other embodiments, components of the sensor system including gateway110 may utilize external power, for example from the engine of a tractorpulling the trailer, from a land power source for example on a pluggedin recreational vehicle or from a building power supply, among otheroptions.

External power may further allow for recharging of energy storagesystems such as batteries to allow the sensor system components such asgateway 110 to then operate in a power limited mode again. Rechargingmethods may also include other power sources, such as, but not limitedto, solar, electromagnetic, acoustic or vibration charging.

The sensor system from FIG. 1 may be used in a variety of environments.One example environment in which the sensor system may be used is shownwith regard to FIG. 2.

Referring to FIG. 2, three sensor systems, namely sensor system 210,sensor system 212, and sensor system 214 are provided.

In the example of FIG. 2, the sensor system 210 may communicate througha cellular base station 220 or through an access point 222. The accesspoint 222 may be any wireless communication access point.

Further, in some embodiments, the sensor system 210 could communicatethrough a wired access point such as Ethernet or fiber, among otheroptions.

The communication may then proceed over a wide area network such as aninternet 230 and proceed to servers 240 or 242.

Similarly, the sensor system 212 and sensor system 214 may communicatewith servers 240 or server 242 through one or both of the base station220 or access point 222, among other options for such communication.

In other embodiments, any one of sensor systems 210, 212 or 214 maycommunicate through satellite communication technology. This, forexample, may be useful if the sensor system is travelling to areas thatare outside of cellular coverage or access point coverage.

In other embodiments, the sensor system 212 may be out of range of theaccess point 222, and may communicate with the sensor system 210 toallow sensor system 210 to act as a relay for communications.

Communication between the sensor system 210 and server 240 may beunidirectional or bidirectional. Thus, in one embodiment the sensorsystem 210 may provide information to server 240 but server 240 does notrespond. In other cases, server 240 may issue commands to the sensorsystem 210 but data may be stored internally on sensor system 210 untilthe sensor system arrives at a particular location. In other cases,two-way communication may exist between the sensor system 210 and server240.

A server, central server, processing service, endpoint, Uniform ResourceIdentifier (URI), Uniform Resource Locator (URL), back-end, and/orprocessing system may be used interchangeably in the descriptionsherein. The server functionality typically represents dataprocessing/reporting that are not closely tied to the location of thesensor systems 210, 212, 214, etc. For example, the server may belocated essentially anywhere so long as it has network access tocommunicate with the sensor systems 210, 212, 214, etc.

Server 240 may, for example, be a fleet management centralizedmonitoring station. In this case, server 240 may receive informationfrom sensor systems associated with various trailers or cargocontainers, providing information such as the location/position of suchcargo containers, the temperature within such cargo containers, anyunusual events including sudden decelerations, temperature warnings whenthe temperature is either too high or too low, wheel bearing and tireinformation, among other data. The server 240 may compile suchinformation and store it for future reference. It may further alert anoperator. For example, a sudden deceleration event may indicate that atrailer may have been in an accident and the operator may need to callemergency services and potentially dispatch another tractor to thelocation/position.

In other embodiments, server 240 may be a trailer tracking andmaintenance server which is used to determine how far a trailer hastraveled and whether any parts of the trailer need to be maintained.Maintenance may be scheduled on a time in use basis as well as othermeasured references, such as distance; for example lubrication may bespecified in hours of use or calendar time between replacement orreplenishment.

Other examples of functionality for server 240 are possible.

In the embodiment of FIG. 2, servers 240 and 242 may further have accessto third-party information or information from other servers within thenetwork. For example, a data services provider 250 may provideinformation to the server 240. Similarly, a data repository or database260 may also provide information to the server 240.

For example, the data services provider 250 may be a subscription basedservice used by the server 240 to obtain current or historic road andweather conditions.

The data repository or database 260 may for example provide informationsuch as image data associated with a particular location, aerial maps,detailed street maps, road surface information, or other suchinformation.

The types of information provided by the data service provider 250 orthe data repository or database 260 is not limited to the above examplesand the information provided could be any data useful to the server 240.

In some embodiments, information from the data service provider 250 orthe data repository from database 260 can be provided to one or more ofthe sensor systems 210, 212, or 214 for processing at those sensorsystems.

Utilizing a sensor system such as that described above, in accordancewith the various embodiments of the present disclosure, tire, wheelassembly and wheel bearing performance may be monitored. Further thecondition of ancillary running gear may be ascertained; for example, theperformance of suspension components may be determined from the behaviorof unsprung masses in response to road stimuli in one embodiment.

For example, reference is now made to FIG. 3, which shows a schematicview of a trailer comprising a sensor system. In the embodiment of FIG.3, a trailer 310 is shown having eight wheels 320. One wheel assembly322 is expanded for visibility.

The wheel assembly 322 includes a tire 324, a bearing 326 and an axle328.

The trailer 310 includes a sensor hub 330 which may collect data fromsensors associated with the wheel assembly 322. The sensor hub 330 maythen communicate in a wired or wireless fashion with a sensor gateway332.

In some embodiments, sensors on wheel assembly 322 would communicatedirectly with sensor gateway 332 rather than through a sensor hub 330.

In accordance with the embodiment of FIG. 3, the wheel assembly 322includes at least one TPMS sensor 340. The TPMS sensor 340 may measureand report the temperature and tire pressure within the tire or wheelassembly 322.

The wheel assembly 322 may further include a bearing sensor 342. Forexample, bearing sensor 342 may be a MEMS sensor used to measureacceleration and temperature of the wheel bearings.

Acoustic sensors 344 and 346 are also shown as part of wheel assembly322. The acoustic sensors 344 and 346 may be placed in proximity to thevarious components that are being monitored. The acoustic sensors 344and 346 measure sound emanating from the tires and/or wheel assembly andare therefore pressure wave sensors. In various embodiments, acousticsensors 344 and 346 may include sensors to capture audible sound,sensors to capture ultrasonic sound, or sensors to capture both audibleand ultrasonic sound.

In some cases, the acoustic sensors may be positioned and/or constructedto minimize environmental noise beyond what is being sensed. Inparticular, tire noise is representative of the road surface quality andmay be retrieved from acoustic data collected on the wheel.

The tire noise may be collected and processed as follows. At least oneacoustic sensor is coupled to each wheel or set of wheels at a locationon the vehicle. Thereafter, the acoustic sensor collects data while thevehicle is in motion. The raw acoustic sensor data may be processed, forexample in the frequency domain, to develop a characteristic signatureover each sample period. Such conversion of raw acoustic sensor data mayeither occur on the vehicle, for example at the sensor, sensor hub orgateway, or may be passed as raw data to a server which may then processthe data.

If the data conversion occurs at the trailer, the characteristicsignature data may be aggregated prior to being transmitted to theservers in some embodiments.

The type, number and location of the sensors in FIG. 3 are howevermerely an example. In other embodiments, different types, number andlocations of sensors may be provided.

Utilizing a system such as that described in FIG. 3, sensor data may becollected while a trailer or truck is in service. For example, suchsensor data may be collected at pre-determined intervals such as everyfive minutes. Alternatively, or in addition, the collection of data maybe based on a trigger. A trigger may include the sensing of a suddenimpact force such as a wheel passing over an irregular surface featuresuch as a pothole or a sudden change in environmental temperature suchas when a vehicle may be driving into a snowstorm.

The sensor data may be collected, potentially aggregated or processed,and sent to a central server in one embodiment. The sending of the datamay be supplemented with additional information, such asposition/location of the vehicle, current operational parameters,together with identifying characteristics of the vehicle and its load.

The central server may then store and process the received sensor dataand additional information.

For example, reference is now made to FIG. 4. In the embodiment of FIG.4, the process starts at block 410 and proceeds to block 412 in which acheck is made to determine whether a trigger condition has been met. Asindicated above, the trigger condition may be a time condition. Forexample, sensor data may be collected every five minutes in someembodiments.

In other embodiments, the trigger at block 412 may be a high-impactcondition or environmental condition. Other possibilities for a trigger412 might include load conditions such as the deflection of a loadbearing member or reaching a peak deflection threshold of a suspensioncomponent. A trigger 412 might also be generated on demand from amanagement system server or a manual request from a person such as adriver or rider in the vehicle. Other possibilities would also exist.

If a trigger condition is not met at the check at block 412, the processproceeds to loop back at block 412 until a trigger condition is met.

Once a trigger condition is met, the process proceeds from block 412 toblock 420 in which sensor data is read. Such reading of the sensor datamay, for example, occur at sensor modules or may be directly at thesensor gateway. If the reading is at sensor modules, the data may thenbe propagated to the sensor gateway through wireless or wired techniquesas described above.

From block 420 the process proceeds to block 422 in which acoustic datamay be read. Such acoustic data may, for example, come from acousticsensors 344 or 346 in the embodiment of FIG. 3.

The acoustic data, read within block 422, may be stored or cached in araw format or may be processed at a sensor module or a gateway prior tobeing uploaded to the server. The processing may include a frequencyconversion or derivation, for example using a Fast Fourier Transform.The processing in the frequency domain may develop a characteristicsignature over a sampling period, for example a trend. In this case, thecharacteristic signature data may be aggregated prior to beingtransmitted.

The process then proceeds to block 430, in which global positioningsystem (GPS) or other similar location/position information may be readand associated with the sensor data received at blocks 420 and/or 422.Further, in block 430, other supplemental data may be collected tosupplement the sensor data and improve diagnostic capabilities inaccordance with the embodiments described herein. For example, atimestamp or other identifying information may be attributed to thesensor data, environmental conditions or readings may be placed inassociation with sensor data, camera images may be associated with thesensor data, among other options.

Other sensor data that may be also be added includes brake wear sensors,or acoustic sensors that can detect brake anomalies, strain gauges amongother options.

In still further embodiments, local system data may be collected from avehicle data bus such as, for example, an On-Board Diagnostics (OBD)port to supplement the sensor data. Such data could include engineperformance, vehicle speed, engine temperature, alarms or warningsgenerated by other vehicle subsystems, among other data.

As described below, supplemental information including GPS and mappinginformation may be used to provide intelligent processing of sensorinformation. For example, GPS location information may be used todetermine the location of the truck, and may be used to find roadconditions from a database. Different acoustic signatures may beexperienced during travel on a dirt or gravel road rather than a pavedroad. Further, timestamp information along with GPS information may beused in processing to determine weather information for the vehicle. Ifthe road is snow-covered or wet this may also provide different sensorreadings.

The process then proceeds to block 440 in which the data is cached, andin some cases, may also be processed. The processing at block 440 may,for example, include the acoustic processing described above with regardto the frequency conversions to create characteristic signatures.Further, the processing may involve aggregating data or comparing thedata to a baseline performance level. The baseline performance level mayhave been created by the manufacturer of the vehicle, by previous manualinput, or from accumulated readings and data of the vehicle or similarvehicles within the fleet. Further, in some embodiments baselineperformance data may be provided by a third party. The baseline may bestored locally within a component of the vehicle system or be stored ona server or in the cloud.

The processing may further include compression of the data for bothstoring the data at the sensor module or gateway, and further fortransmitting the data to a server, as described below. The processeddata may be compressed into a compressed form such as a signature orhash. It may also be filtered and a Fast Fourier Transform may be madeto process the data and provide an analysis. Further, compression mayinvolve correlation of information from different sensors or sensormodules.

The compressed raw sensor data may be then provided as a smaller dataset that contains only useful information which may optimize memory chipsizes and minimize communication times.

Further, in some cases, the processing may use stored or historicinformation, or supplemental information.

In one embodiment, the processing may further comprise adding securityto the data. For example, the data may be signed or encrypted to ensurethe authenticity of the data.

From block 440 the process proceeds to block 450 in which a check ismade to determine whether the data needs to be uploaded. For example,the data may be uploaded every six sampling periods in some embodiments.In other cases, data is not uploaded until the vehicle is stationary. Inother cases, the data may only be uploaded in certain geographic areas.In other cases, the data is uploaded at every sampling cycle. Otherexamples are possible.

From block 450, if the data needs to be uploaded then the processproceeds to block 452 in which the data is uploaded to a server.

From block 450 if data does not need to be uploaded, or from block 452,the process returns to block 412 in which the process awaits the nexttrigger condition.

Once the sensor data is collected, it may be processed. The processingmay occur, in some embodiments, at the sensor module or gateway.However, in other embodiments the sensor processing may be done, atleast partially, on the server side. The entity performing suchprocessing is referred to herein as the processing node.

Reference now made to FIG. 5, which shows a process for the analysis ofreceived data. In particular, the process of FIG. 5 starts at block 510and proceeds to block 512 in which check is made to determine whethersensor data has been received. If not, the process continues to loop atblock 512 until sensor data is received.

Once sensor data is received, the process proceeds from block 512 toblock 520 in which supplemental data related to the received data isobtained. For example, if the received data includes a GPS fix(location/position information), the supplemental data obtained at block520 may include the weather conditions for the particular time andlocation that the sensor data was obtained. It may further include mapinformation including a roadway description. It may further includehistoric data obtained from either this particular vehicle or from othervehicles that have travelled on the same roadway. Other examples ofsupplemental data are possible.

The data at block 512 and the supplemental data at block 520 may becollected for a duration of a trip or across multiple trips in someembodiments.

Based on the data received at block 512 and supplemental data at block520, processing may then occur. The data is processed at block 530 inthe embodiment of FIG. 5.

For example, as provided above, TPMS sensor data received at block 512may be used to monitor the state of each of the tires. The air volume ina tire is related to a ratio of temperature and pressure. If the tire isnot losing air, the ratio should remain constant. If the ratio changesover time, this could relate to air pressure loss in the tire. Comparinginformation between adjacent wheels may allow the detection of uneventire wear.

Similarly, bearing sensors could record temperature and vibrationrepresenting roughness or wear in the wheel bearings. Sensormeasurements that show increased temperature or vibration beyond thenormal operation could trigger the system to alert an operator.

Acoustic sensors could record the sound of the wheel assembly and derivea characteristic signature over a sampling interval. For example, asampling interval may be in the order of 10 to 20 seconds. In this case,a characteristic signature based on an analysis of the acoustic input inthe frequency domain could be developed.

In some embodiments, an acoustic base line may be created, for example,using a vehicle that is known to be in good condition. Such acousticbase line may then be used for processing of acoustic signals. However,as described above, in other embodiments the base line could be acquiredin different ways.

The processing could, in some embodiments, consider the status of otherwheel assemblies. Thus, if bearing sensors at one wheel assembly areproviding higher temperature or vibration readings, this may indicatethat the bearing may be at risk of failure, for example.

The processing could consider supplemental information, eitherassociated with the data received at block 512 or obtained at block 520.

For example, in one embodiment the supplemental data received at block512 could include a location/position fix and a timestamp. Based on thisinformation, weather conditions for the location of the vehicle(trailer) could be determined at block 520. Such weather conditionscould indicate that the temperature in the area of the vehicle wasextremely cold, and this could be used in conjunction with the TPMSreadings.

In other embodiments, the supplemental data received at block 512 couldbe a position/location fix for the vehicle (trailer). Such aposition/location fix could then be used at block 520 to determine thata stretch of road is being repaved and thus the acoustic informationreceived at block 512 should consider the altered road noise.

In still further embodiments, the supplemental information could includea camera picture showing a snow-covered roadway. Image processing atblock 530 could then use the image data for processing the sensor data.Other options are possible.

In some embodiments, other supplemental data can also be used. Forexample, if the trailer is carrying a load of animals, such informationmay be provided to the processing node and the noise generated by suchanimals may also be filtered out. Other examples of filtering usingsupplemental data are also possible.

In other embodiments, supplemental data can include load information.For example, information from sensors such as a strain gage sensor onthe suspension or a sensor on an air suspension component may provideinformation regarding the load, which may then allow factors that affectwheel assembly performance, such as unbalanced load, to be factored intothe processing at block 530.

The processing at block 530 may provide for alarm conditions if acomponent is on the verge of failure. Therefore, the process proceeds toblock 540 and checks whether an alarm condition exists. If yes, thealarm condition may be posted at block 542. Such posting may includealerting an operator of the vehicle, a transportation company, otherdrivers within the company and other drivers of vehicles within thevicinity, among other users of the system.

The alarm at block 542 could be categorized into various levels. Forexample, the alarm could indicate to a user to stop the vehicleimmediately. In other cases, the alarm could indicate that the vehicleshould stop in a certain time period or a certain distance. For example,the data may indicate that the vehicle should stop in the next 10,000km, within the next 10 km, or immediately.

From block 540 if an alarm condition does not exist, or from block 542,the process may then proceed to block 550 in which the data is recordedand stored.

The process may then proceed to block 560 in which the recorded data isprocessed with regard to historic data. The processing at block 560 maylook for trends over time that may lead to failure of a vehicle'sbearings or tires. Further, the data may be aggregated from manyvehicles to better predict maintenance and failure conditions. Suchpredictions can be used to schedule future maintenance appointmentswithin the fleet management server/system, or by sending data to anexternal server/system.

Further, the ability to process the data from multiple sensors to defineand calibrate the behavior for normal operations and use supplementaldata to better predict anomalous conditions and trends allows for betterprediction of the failure of the wheel assembly, bearing or tire.

The comparison of the sensor data with historical data may allow forpreventative maintenance to occur, rather than a failure. The comparisonof sensor data with historical data also allows the system toautomatically detect when maintenance has occurred or parts replaced dueto sudden better data. Data that maintenance has occurred may also beinput manually and used to reset or restart trend analysis from thatpoint in time.

The historical processing at block 560 could create a warning conditionto warn an operator to inspect their vehicle after the completion of thetrip. This is shown for example with block 570 in which a check is madeto determine whether warning exists and if yes, the process proceeds toblock 572 in which the warning is posted to the operator, for example.

From block 570 or block 572 the process then proceeds back to block 512in which new data from sensors is potentially received.

The processing at blocks 530 and 560 could utilize templates to allowfor better processing. Such templates could be developed to allow forthe identification that not only a change in the performance of thebearing or tire has occurred, but it could categorize the nature of thechange. For example, in some cases, the readings of the tires andbearings could indicate that a load has shifted and this may lead tofailure prediction.

In accordance with the above, the use of the historic data as well asthe current data may provide for component failure prediction, which mayallow for scheduled maintenance rather than unscheduled maintenance oncomponent failure. This is typically cheaper in the transport industry.The historic data may also be used to determine if potential failurepredictions from the current data are in themselves anomalous and onlyrequire a cursory check or the re-setting of a false sensor trigger.

A server performing the processing of FIG. 5 may be a server such asserver 240 or 242. Such server may be any network node. For example, onesimplified server that may perform the embodiments described above isprovided with regards to FIG. 6.

In FIG. 6, server 610 includes a processor 620 and a communicationssubsystem 630, where the processor 620 and communications subsystem 630cooperate to perform the methods of the embodiments described herein.

The processor 620 is configured to execute programmable logic, which maybe stored, along with data, on the server 610, and is shown in theexample of FIG. 6 as memory 640. The memory 640 can be any tangible,non-transitory computer readable storage medium, such as optical (e.g.,CD, DVD, etc.), magnetic (e.g., tape), flash drive, hard drive, or othermemory known in the art. In one embodiment, processor 620 may also beimplemented entirely in hardware and not require any stored program toexecute logic functions.

Alternatively, or in addition to the memory 640, the server 610 mayaccess data or programmable logic from an external storage medium, forexample through the communications subsystem 630.

The communications subsystem 630 allows the server 610 to communicatewith other devices or network elements.

Communications between the various elements of the server 610 may bethrough an internal bus 660 in one embodiment. However, other forms ofcommunication are possible.

The embodiments described herein are examples of structures, systems ormethods having elements corresponding to elements of the techniques ofthis application. This written description may enable those skilled inthe art to make and use embodiments having alternative elements thatlikewise correspond to the elements of the techniques of thisapplication. The intended scope of the techniques of this applicationthus includes other structures, systems or methods that do not differfrom the techniques of this application as described herein, and furtherincludes other structures, systems or methods with insubstantialdifferences from the techniques of this application as described herein.

While operations are depicted in the drawings in a particular order,this should not be understood as requiring that such operations beperformed in the particular order shown or in sequential order, or thatall illustrated operations be performed, to achieve desirable results.In certain circumstances, multi-tasking and parallel processing may beemployed. Moreover, the separation of various system components in theimplementation descried above should not be understood as requiring suchseparation in all implementations, and it should be understood that thedescribed program components and systems can generally be integratedtogether in a signal software product or packaged into multiple softwareproducts. In some cases, functions may be performed entirely in hardwareand such a solution may be the functional equivalent of a softwaresolution

Also, techniques, systems, subsystems, and methods described andillustrated in the various implementations as discrete or separate maybe combined or integrated with other systems, modules, techniques, ormethods. Other items shown or discussed as coupled or directly coupledor communicating with each other may be indirectly coupled orcommunicating through some interface, device, or intermediate component,whether electrically, mechanically, or otherwise. Other examples ofchanges, substitutions, and alterations are ascertainable by one skilledin the art and may be made.

While the above detailed description has shown, described, and pointedout the fundamental novel features of the disclosure as applied tovarious implementations, it will be understood that various omissions,substitutions, and changes in the form and details of the systemillustrated may be made by those skilled in the art. In addition, theorder of method steps is not implied by the order they appear in theclaims.

When messages are sent to/from an electronic device, such operations maynot be immediate or from the server directly. They may be synchronouslyor asynchronously delivered, from a server or other computing systeminfrastructure supporting the devices/methods/systems described herein.The foregoing steps may include, in whole or in part,synchronous/asynchronous communications to/from thedevice/infrastructure. Moreover, communication from the electronicdevice may be to one or more endpoints on a network. These endpoints maybe serviced by a server, a distributed computing system, a streamprocessor, etc. Content Delivery Networks (CDNs) may also provide mayprovide communication to an electronic device. For example, rather thana typical server response, the server may also provision or indicate adata for content delivery network (CDN) to await download by theelectronic device at a later time, such as a subsequent activity ofelectronic device. Thus, data may be sent directly from the server, orother infrastructure, such as a distributed infrastructure, or a CDN, aspart of or separate from the system.

Typically, storage mediums can include any or some combination of thefollowing: a semiconductor memory device such as a dynamic or staticrandom access memory (a DRAM or SRAM), an erasable and programmableread-only memory (EPROM), an electrically erasable and programmableread-only memory (EEPROM) and flash memory; a magnetic disk such as afixed, floppy and removable disk; another magnetic medium includingtape; an optical medium such as a compact disk (CD) or a digital videodisk (DVD); or another type of storage device. Note that theinstructions discussed above can be provided on one computer-readable ormachine-readable storage medium, or alternatively, can be provided onmultiple computer-readable or machine-readable storage media distributedin a large system having possibly plural nodes. Such computer-readableor machine-readable storage medium or media is (are) considered to bepart of an article (or article of manufacture). An article or article ofmanufacture can refer to any manufactured single component or multiplecomponents. The storage medium or media can be located either in themachine running the machine-readable instructions, or located at aremote site from which machine-readable instructions can be downloadedover a network for execution.

In the foregoing description, numerous details are set forth to providean understanding of the subject disclosed herein. However,implementations may be practiced without some of these details. Otherimplementations may include modifications and variations from thedetails discussed above. It is intended that the appended claims coversuch modifications and variations.

1-21. (canceled)
 22. A method at a server for maintenance scheduling fora moving platform, the method comprising: receiving sensor data for theat least one component of the moving platform, along with supplementaldata associated with the moving platform, at the server; processing thesensor data, the processing using the supplemental data to filter thesensor data, wherein the supplemental data comprises at least one of: alocation fix, a time stamp, an image from a camera on the movingplatform, a temperature, a pressure, weather conditions, mapinformation, historic data from the moving platform, historic data froma different moving platform, or load information; and updating amaintenance schedule based on the processing.
 23. The method of claim22, wherein the processing detects an improvement in the performance ofthe at least one component indicating maintenance has been performed onthe at least one component, and wherein the updating reschedules futuremaintenance of the at least one component based on the detection of theimprovement.
 24. The method of claim 22, wherein the processing finds anincreased risk of failure of the at least one component, and wherein theupdating reschedules maintenance of the at least one component to anearlier time.
 25. The method of claim 22, wherein the at least onecomponent is a wheel assembly, and wherein the sensor data comprisesdata from at least one of: a bearing sensor; a tire pressure monitoringsensor; or an acoustic sensor.
 26. The method of claim 25, whereinsensor data from the bearing sensor includes at least one of vibrationor temperature data.
 27. The method of claim 26, wherein the processingcomprises comparing sensor data from the wheel assembly with sensor datafrom at least one other wheel assembly on the moving platform.
 28. Themethod of claim 22, wherein the supplemental data includes the locationfix and the timestamp, and wherein the processing comprises: retrievingweather conditions based on the location fix and timestamp; andfiltering the sensor data based on the weather conditions.
 29. Themethod of claim 22, wherein the supplemental data includes the positionfix, and wherein the processing comprises: retrieving road informationbased on the position fix; and filtering the sensor data based on theroad information.
 30. The method of claim 22, wherein the supplementaldata is an image from a camera on the moving platform, and wherein theprocessing comprises: performing image processing to determine roadconditions; and filtering the sensor data based on the determined roadconditions.
 31. The method of claim 22, further comprising usinghistorical data from at least one of the moving platform or a fleet ofmoving platforms to further process the sensor data.
 32. A server formaintenance scheduling for a moving platform, the server comprising: aprocessor; and a communications subsystem, wherein the processing nodeis configured to: receive sensor data for the at least one component ofthe moving platform, along with supplemental data associated with themoving platform; process the sensor data, the processing using thesupplemental data to filter the sensor data, wherein the supplementaldata comprises at least one of: a location fix, a time stamp, an imagefrom a camera on the moving platform, a temperature, a pressure, weatherconditions, map information, historic data from the moving platform,historic data from a different moving platform, or load information; andupdate a maintenance schedule based on the processing.
 33. The server ofclaim 32, wherein the server is configured to process by detecting animprovement in the performance of the at least one component indicatingmaintenance has been performed on the at least one component, andwherein the server reschedules future maintenance of the at least onecomponent based on the detection of the improvement.
 34. The server ofclaim 32, wherein the server is configured to process by finding anincreased risk of failure of the at least one component, and wherein theserver reschedules maintenance of the at least one component to anearlier time.
 35. The server of claim 32, wherein the at least onecomponent is a wheel assembly, and wherein the sensor data comprisesdata from at least one of: a bearing sensor; a tire pressure monitoringsensor; or an acoustic sensor.
 36. The server of claim 35, whereinsensor data from the bearing sensor includes at least one of vibrationor temperature data.
 37. The server of claim 36, wherein the processingnode is configured to process by comparing sensor data from the wheelassembly with sensor data from at least one other wheel assembly on themoving platform.
 38. The server of claim 32, wherein the supplementaldata includes a location fix and a timestamp, and wherein the processingnode is configured to process by: retrieving weather conditions based onthe location fix and timestamp; and filtering the sensor data based onthe weather conditions.
 39. The server of claim 32, wherein thesupplemental data includes a position fix, and wherein the processingnode is configured to process by: retrieving road information based onthe position fix; and filtering the sensor data based on the roadinformation.
 40. The server of claim 32, wherein the supplemental datais an image from a camera on the moving platform, and wherein theprocessing node is configured to process by: performing image processingto determine road conditions; and filtering the sensor data based on thedetermined road conditions.
 41. The server of claim 32, wherein theprocessing node is further configured to use historical data from atleast one of the moving platform or a fleet of moving platforms tofurther process the sensor data.
 42. A computer readable medium forstoring instruction code, which, when executed by a processor on aserver are configured for maintenance scheduling for a moving platform,the instruction code causing the processing node to: receive sensor datafor the at least one component of the moving platform, along withsupplemental data associated with the moving platform; process thesensor data, the processing using the supplemental data to filter thesensor data, wherein the supplemental data comprises at least one of: alocation fix, a time stamp, an image from a camera on the movingplatform, a temperature, a pressure, weather conditions, mapinformation, historic data from the moving platform, historic data froma different moving platform, or load information; and update amaintenance schedule based on the processing.